Model comparison
GLM-4.5 vs GPT-5.2
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-4.5 #68 (Estimated); GPT-5.2 #64 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.5 and GPT-5.2 share 1 comparable benchmark result. 0 of 8 categories are comparable. 0 results are unique to GLM-4.5; 27 to GPT-5.2.
Updated July 20, 2026- Shared results
- 1
- GLM-4.5 only
- 0
- GPT-5.2 only
- 27
- Comparable categories
- 0 / 8
Benchmark data for GLM-4.5 and GPT-5.2 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
GPT-5.2 is priced at $1.75 input / $14.00 output per 1M tokens, versus $0.60 input / $2.20 output per 1M tokens for GLM-4.5. GPT-5.2 has the larger context window at 400K, compared with 128K for GLM-4.5.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GLM-4.5 | Δ | GPT-5.2 |
|---|---|---|---|
| Agentic | GLM-4.5Not measured | MarginNo overlap | GPT-5.255.7 |
| Coding | GLM-4.5Not measured | MarginNo overlap | GPT-5.270.6 |
| Reasoning | GLM-4.5Not measured | MarginNo overlap | GPT-5.252.9 |
| Knowledge | GLM-4.5Not measured | MarginNo overlap | GPT-5.292.4 |
| Math | GLM-4.5Not measured | MarginNo overlap | GPT-5.235.2 |
| Multimodal | GLM-4.5Not measured | MarginNo overlap | GPT-5.280.4 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.5 | GPT-5.2 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.5$0.6 input / $2.2 output | GPT-5.2$1.75 input / $14 output | GLM-4.5 has the lower combined listed price. |
| Generation speedtokens per second | GLM-4.551 tok/s | GPT-5.273 tok/s | GPT-5.2 has the higher measured throughput. |
| First-answer latencyseconds to first token | GLM-4.51.45 s | GPT-5.2130.34 s | GLM-4.5 reaches the first token sooner. |
| Context windowmaximum listed tokens | GLM-4.5128K | GPT-5.2400K | GPT-5.2 lists the larger context window. |
Benchmark Deep Dive
Agentic5 benchmarks
Coding4 benchmarks
Reasoning3 benchmarks
Knowledge7 benchmarks
| Benchmark | GLM-4.5 | GPT-5.2 | Result |
|---|---|---|---|
| GPQASource | — | 92.4% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 42.2% | Not comparable |
| AA-GPQA DiamondSource | — | 90.3% | Not comparable |
| AA-HLESource | — | 35.4% | Not comparable |
| AA-Omniscience IndexSource | — | -1.0% | Not comparable |
| AA-Omniscience AccuracySource | — | 43.8% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 79.7% | Not comparable |
Math3 benchmarks
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | GLM-4.5 | GPT-5.2 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 75.4% | Not comparable |
Frequently Asked Questions (3)
Can I compare GLM-4.5 and GPT-5.2 on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for GLM-4.5 and GPT-5.2 today?
GLM-4.5: $0.60 input / $2.20 output per 1M tokens GPT-5.2: $1.75 input / $14.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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